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There is consensus that visible haematuria may be a sign of serious underlying disease, including malignancy, and warrants a thorough diagnostic evaluation. This is usually undertaken by a combination of clinical examination, cystoscopic evaluation, and urinary tract imaging.  A decision support tool has been developed in the form of an algorithmic flow chart as part of a suite of on-line evidence-based and consensus-based guidelines Diagnostic Imaging Pathways (DIP):  www.imagingpathways.health.wa.gov.au  (Online clinical decision-making tool: Dulku G. Painless Macroscopic Haematuria. Diagnostic Imaging Pathways; September 2015) to provide imaging recommendations for adult patients with unexplained, painless visible haematuria. A literature review, including reference to several international consensus-based expert guidelines, has been employed to develop this tool.  The choice of first line imaging method is dependent on the risk stratification into high or low risk for the development of renal and urologic malignancies. Ultrasound is vital in the initial assessment of haematuria particularly in radiation sensitive patients, low-risk patients, and in young men <40 years. Computed tomographic urography (CTU) is a sensitive and specific method for the detection of urothelial malignancy particularly in high-risk patients. Magnetic resonance urography (MRU) provides better contrast resolution than CTU without exposure to ionising radiation or requiring intravenous (IV) contrast administration, making it more suitable for examination of paediatric and pregnant patients and patients with renal impairment. Cystoscopy remains the gold standard in the detection of lower urinary tract (bladder) urothelial tumours.  Until randomised clinical trials comparing different diagnostic modalities or strategies prospectively and outcome studies are available, consensus-based practice recommendations similar to ours are nonetheless warranted to reduce the variation in haematuria management.

Painless Visible Haematuria in Adults: An Algorithmic Approach Guiding Management